up

config_examples/freqaiprimer.json

@@ -8,7 +8,7 @@
     "tradable_balance_ratio": 1,
     "fiat_display_currency": "USD",
     "dry_run": true,
-    "timeframe": "3m",
+    "timeframe": "5m",
     "dry_run_wallet": 1000,
     "cancel_open_orders_on_exit": true,
     "stoploss": -0.05,

freqtrade/templates/freqaiprimer.py

@@ -12,7 +12,7 @@ from freqtrade.strategy import IStrategy
 logger = logging.getLogger(__name__)
 
 
-class DivergenceRegressionStrategy(IStrategy):
+class FreqaiPrimer(IStrategy):
     """
     策略说明：
         - 所有交易信号基于 FreqAI 的动态预测
@@ -124,6 +124,17 @@ class DivergenceRegressionStrategy(IStrategy):
         for col in columns_to_clean:
             dataframe[col] = dataframe[col].replace([np.inf, -np.inf], 0).ffill().fillna(0)
 
+        columns_to_clean = [
+            "%-rsi-period", "%-mfi-period", "%-sma-period", "%-ema-period", "%-adx-period",
+            "bb_lowerband-period", "bb_middleband-period", "bb_upperband-period",
+            "%-bb_width-period", "%-roc-period", "%-relative_volume-period", "%-close-bb_lower-period", "%-tema-period",
+            "%-price_trend_diff-period", "%-roc_mfi_ratio-period"
+        ]
+
+        for col in columns_to_clean:
+            dataframe[col] = dataframe[col].replace([np.inf, -np.inf], np.nan)
+            dataframe[col] = dataframe[col].ffill().fillna(0)
+
         return dataframe
 
     # 👇 定义目标列（全部为连续值）
@@ -151,6 +162,20 @@ class DivergenceRegressionStrategy(IStrategy):
         dataframe["trend_change"] = dataframe["&-trend_strength"].pct_change(label_period)
         dataframe["&-divergence_score"] = dataframe["price_change"] - dataframe["trend_change"]
 
+        # 👇 新增：清理所有目标列中的非有限值
+        target_columns = [
+            "&-trend_strength",
+            "&-volatility_forecast",
+            "&-roi_target",
+            "&-stoploss_target",
+            "&-divergence_score"
+        ]
+
+        for col in target_columns:
+            if col in dataframe.columns:
+                dataframe[col] = dataframe[col].replace([np.inf, -np.inf], np.nan)
+                dataframe[col] = dataframe[col].ffill().fillna(0)
+
         return dataframe
 
     # 👇 缓存 mean/std 供后续使用